This paper presents a random seed nearest neighbour search clustering algorithm (RS-NNS). The method is to follow the nearest neighbours'' direction of a random selected seed, search and find its neighbours which have the greatest similar features, form the local maximum cluster, adjust dynamically the data objects'' belongingness to realize the local optimization, and end the clustering procedure until all the data objects are identified. Experiments verify that the new algorithm fits the problems such as different density, shape, noise, cluster number and so on, and can realize fast optimization searching.